Non-destructive estimation of maize leaf area, fresh weight, and dry weight using leaf length and leaf width

Transcription

1 Communcatons n Bometry and Crop Scence Vol. 5, o. 1, 2010, pp Internatonal Journal of the Faculty of Agrculture and Bology, Warsaw Unversty of Lfe Scences, Poland REGULAR ARTICLE on-destructve estmaton of maze leaf area, fresh weght, and dry weght usng leaf length and leaf wdth Hassan Mokhtarpour 1 *,**, Chrstopher B.S. Teh 2, Ghzan Saleh 3, Ahmad B. Selamat 3, Mohammad E. Asad 4, Behnam Kamkar 5 1 Agrcultural and atural Resources Research Center of Golestan, Iran. 2 Department of Land Management, Faculty of Agrculture, Unversty Putra Malaysa. 3 Department of Crop Scence, Faculty of Agrculture, Unversty Putra Malaysa. 4 Department of Agrcultural Engneerng, Agrcultural and atural Resources Research Center of Golestan, Iran. 5 Department of Agronomy, Faculty of Agrculture, Gorgan Unversty of Agrcultural Scences and atural Resources. * Correspondng author: H. Mokhtarpour, E-mal: mokhtarpour2009@yahoo.com ** Current address: Department of Land Management, Faculty of Agrculture, Unversty Putra Malaysa. CITATIO: Mokhtarpour, H., Teh, C.B.S., Saleh, G., Selmat, A.B., Asad, M.E., Kamar, B. (2010). on-destructve estmaton of maze leaf area, fresh weght, and dry weght usng leaf length and leaf wdth. Communcatons n Bometry and Crop Scence 5 (1), Receved: 5 May 2009, Accepted: 18 May 2010, Publshed onlne: 26 May 2010 CBCS 2010 ABSTRACT Leaf area and leaf weght measurements are requred to calculate several growth ndces, whch are leaf area ndex (LAI), net assmlaton rate (AR), specfc leaf area (SLA), specfc leaf weght (SLW), and leaf area duraton (LAD). We developed three predctve equatons to estmate leaf area, leaf fresh and dry weght n maze from leaf length and leaf wdth measurements. A total of 1,314 leaves from dfferent parts of plants at dfferent plant growth stages, dfferent plantng denstes and dfferent sowng dates were collected n 2008 at the Agrcultural Research Center near Gorgan, Golestan, Iran. To evaluate the equatons, some goodness of ft ndcators used ncluded mean absolute error, root mean square error and ndex of agreement. Ths study found strong relatonshps between leaf length and leaf wdth and LA, LFW and LDW (R 2 > 0.85). Based on the results LA, LFW and LDW of ndvdual maze leaves can be estmated non-destructvely by leaf length and leaf wdth. These equatons allow the research workers to make non-destructve or repeat measurements on the same leaves. The general equaton to estmate LA, LFW, and LDW was: Ln (Y) = a + b Ln (L) + c Ln (W). Key Words: Zea mays; maze; leaf area; leaf fresh weght; leaf dry weght; non-destructve estmaton.

2 20 Communcatons n Bometry and Crop Scence, 5(1) ITRODUCTIO Leaf area (LA) plays an mportant role n plant growth analyss. Leaf area and leaf weght measurements are requred to calculate several growth ndces, whch are leaf area ndex (LAI), net assmlaton rate (AR), specfc leaf area (SLA), specfc leaf weght (SLW), and leaf area duraton (LAD) (Gardner et al., 1985). There are varous methodologcal approaches to measure plant leaf area. Drect measurement of leaf area s usually tme consumng and labor ntensve and ths acton usually causes canopy damage. But leaf area can be estmated non-destructvely by usng mathematcal formulae, whch only requre smple measurements of the leaf lamna. Potdar and Pawar (1991) evaluated non-destructve leaf area estmaton n banana (Musa acumnata Colla.) and showed a strong relatonshp between leaf area and varous combnatons of leaf length (L) and leaf wdth (W). Pekson (2007) also showed that there was a hgh correlaton between leaf area and a combnaton of lamna length (L) and lamna wdth (W) n Vca faba L. Serdar and Demrsoy (2006) developed a mathematcal equaton to estmate leaf area n chestnut (Castanea sp.) by measurng leaf length and leaf wdth and calculated dfferent combnaton of them. Ther result showed that there was a strong relatonshp between estmated leaf area and actual leaf area (R 2 = 0.99). Cho et al. (2007) found that estmaton of ndvdual LA, leaf fresh weght (LFW) and LDW n hydroponcally grown cucumbers (Cucums satvus L.) can be done wth hgh accuracy usng leaf length leaf wdth and leaf chlorophyll value (R 2 = 0.98, R 2 = 0.96, R 2 = 0.96 respectvely). Montgomery (1911), cted n McKee (1964), Pearce et al. (1975), and Dwyer and Stewart (1986), reported a general equaton to estmate ndvdual leaf area of maze (Zea mays L.): Leaf area = L W A where LA, L, W, and A are leaf area, leaf length, leaf maxmum wdth and a constant (A = 0.75), respectvely. Other researchers obtaned A values between 0.72 and 0.79, for example 0.72 (Keatng and Wafula, 1992), 0.73 (McKee, 1964; Dwyer and Stewart, 1986; Stewart and Dwyer, 1999), and 0.79 (Brch et al., 1998). McKee (1964) proposed that total leaf area may be estmated by multplyng the sum of the lengths of all leaves on a plant by Pearce et al. (1975) proposed multplyng the area of the eghth leaf from the top by Elngs (2000) showed that f the total number of leaves of tropcal maze and area of the largest leaf are known, total plant leaf area can be estmated drectly, makng use of the fact that the area of the largest leaf relatve to total plant leaf area s constant, and that ths constant s lnearly related to total leaf number. The objectves of the current study were to develop equatons to estmate leaf area (LA), leaf fresh weght (LFW), and leaf dry weght (LDW) of maze from leaf length and wdth. The accuracy of the equatons was tested on maze at varous plantng denstes, plant growth stages and plantng dates. The equaton developed to estmate leaf area was tested aganst equatons from other studes. MATERIALS AD METHODS To evaluate non-destructve LA, LFW, and LDW estmaton for four maze plantng dates, three plantng denstes, and four plant growth stages, all leaves from 144 plants were selected from an experment conducted at the Agrcultural Research Center near Gorgan, Golestan, Iran (36 53', 54 21' E) n 2008 to evaluate the effect of plantng date and densty on yeld and yeld components of maze. Plantng dates ncluded 19 Aprl, 4 May, 19 May and 3 June. Plant denstes were 45,000, 65,000 and 85,000 plants ha -1 and plant growth stages were the 5-leaf stage, when the 6th leaf appears but t s too small to measure (V3), 8-leaf stage, when the 9th leaf appears but t s too small to measure (V6), tassel appearance stage (flag leaf was not counted) and mlk stage. Each plot contaned four rows, 12 m n length. The dstance between rows was 75 cm and plantng denstes were changed wth changng dstance between plants row -1. Dstance between plants row -1 was 30, 20, 15.7 cm for plantng

3 Mokhtarpour et al. on-destructve estmaton of maze leaf area and weght 21 denstes 45000, 65000, and 85000, plant ha -1, respectvely. The experments were planted manually n four complete blocks. Three seeds were planted n each hole and then thnned to one plant at the 2-leaf stage so survved plants were same wth ntended plantng denstes. Experment was conducted wthout any water and nutrent lmtaton. Sol water was kept over 50% of feld capacty durng the growng season by furrow rrgaton. Fertlzers were appled based on sol test results. A broadcast applcaton of kg ha -1 (-P-K) was ncorporated nto the seedbed. Addtonal 100 kg ha -1 was appled as sde dressng at 5 and 9-leaf stage (50 kg ha -1 at each stage). Weeds and nsects were adequately controlled durng the growng seasons. In order to measure leaf length, leaf wdth, and leaf area n each treatment, at each harvest, three plants were cut at ground level from three replcatons consderng border effects (one plant from each replcaton). Leaf length and maxmum leaf wdth of all leaves on each plant were measured manually, and the leaf area of each leaf was then measured usng the Area Measurement System (Delta-T Devces Ltd, Cambrdge, UK). Leaf fresh weght of each leaf was measured mmedately after t was removed from the stalk. Leaves were dred to a constant weght at 75 C for about three days. A total of 1,368 leaves from 114 plants (four plantng dates three plant denstes four plant growth stages three plants n each samplng) were collected for ths study. The data from 54 leaves were not recorded due to mechancal damages to leaves durng samplng tme n dfferent treatments and partal leaf senescence after anthess. So a total of 1,314 leaves were used n ths study. The data from 855 leaves (approxmately two thrd of total leaves) were selected at random and pooled wthout consderng plantng date, plant densty and plant growth stages. Curve-fttng software, Table Curve 3D (verson 4; Systat, Inc, Chcago, IL, USA), was used to ft the best equaton for estmaton of LA, LFW, LDW. To evaluate the accuracy of the equatons data from the other 459 leaves (approxmately one thrd of total leaves) were used to test whether the equatons developed could predct LA, LFW, and LDW wth hgh accuracy at dfferent plantng dates, plant denstes and plant growth stages; Model valdty was tested usng three goodness of ft ndcators, the mean absolute error (MAE), the root mean square error (RMSE) (Kobayash and Salam, 2000), and the ndex of agreement (d) (Wllmott et al., 1985). Ther formulae are as follows: RMSE = 1 = 2 ( y yˆ ) y yˆ = MAE = 1 d = 1 ( yˆ y + y y ) = 1 = 1 y yˆ where y and ŷ are the observed and predcted y values, respectvely, and y s the mean of the entre of observed y values. Low values of RMSE and MAE llustrate hgh accuracy whereas hgh d ndcates hgh accuracy. RESULTS AD DISCUSSIO EQUATIO DEVELOPMET We used three crtera to select the best-fttng functon for the data n the 850-leaf tranng set: (1) the functon wth a close degree of ft to the data set as ndcated by a hgh R 2 : (2) the functon shows no overall estmaton or predcton bas; and (3) the functon s parsmonous (Burnham and Anderson, 2002). The latter crteron means the functon fts the

4 22 Communcatons n Bometry and Crop Scence, 5(1) data set closely wth the least number of functon parameters. A parsmonous functon avods "over-fttng" a gven data set. The danger of over-fttng s the functon descrbes random error nstead of the underlyng relatonshp. Such a functon wll ft the tranng set almost perfectly whle havng lttle predctve value, beng too senstve to fluctuatons n the data set (see Hunts and Parsons, 1977). Both leaf length and leaf wdth had a strong relatonshp wth leaf area and LFW wth hgh coeffcents of determnaton (R ) and ndex of agreement d 0.91 (Table 1). Leaf dry weght (LDW) was not estmated as accurately as leaf area and LFW (R 2 = 0.88, d = 0.834). The lower estmated accuracy of LDW could be due to dfferences n the specfc leaf area (SLA) at dfferent plant growth stages. Table 1. Equatons developed for estmatng maze leaf area, leaf fresh weght and leaf dry weght, usng a tranng set of 853 leaves, whch were drawn from a total of 1314 leaves representng four seedng dates, three plant denstes, four growth stages and three plants for each combnaton of these factors. All varables n the models above are sgnfcant at P = Response varable Intercept Ln(leaf length) Ln(leaf wdth) Ln (leaf trat) Estmate SE Estmate SE Estmate SE R 2 P-value Area (LA), cm <0.001 Fresh weght (LFW) <0.001 Leaf Dry weght (LDW) <0.001 EQUATIO EVALUATIO To evaluate the accuracy of the equatons, three goodness-of-ft-ndcators (RMSE, MAE, and d) were determned for treatment factors plant densty, plant growth stage, and plantng date usng a valdaton set of 459 leaves that were not part of the tranng data set. The hghest and lowest values for RMSE, MAE, and d for leaf area were found among growth stages (Table 2). The ndex of agreement exceeded 0.90 n all cases. Accordng to Bland and Altman (1986), cted n Peksen (2007), lack of agreement between predcted values and measured values were evaluated by calculatng the relatve bas, estmated by the mean of dfferences (MD) and the standard devaton of a dfference (SD). When the dfferences are dstrbuted normally, 97 % of the dfferences should be between MD ± (3 SD). There was a lnear relatonshp n the valdaton data set of 459 leaves between measured leaf area and leaf area predcted on the bass of the equaton developed from the tranng data set of 855 leaves (Fg. 1 top row, left panel; Table 2) wth an ndex of agreement of nety-nne percent of the dfferences between measured and predcted leaf areas were wthn ± 3 SD of the mean dfference (Fg. 1 top row, rght panel), whch s n agreement wth normal dstrbuton theory. However, the graph also ndcates that the dfference ncreased wth ncreasng leaf area. The predcton of leaf fresh weght wth the predcton formula developed n the frst step worked qute well wth d-values 0.88 (Table 3). The graph of measured vs. predcted based on pooled data of 459 leaves n the valdaton set ndcates that the actual relatonshp may be curvlnear (Fg. 1 mddle row, left panel) and assessment that s supported by the plot of dfferences between measured and predcted values (Fg. 1 mddle row, rght panel). The ndex of agreement between measured and predcted leaf dry weght was lower than the ndex for leaf area and leaf fresh weght. It ranged from d = 0.71 at the gran fllng stage to d = 0.84 for the frst and thrd plantng date (Table 4). Ths s borne out by the graph,

5 Mokhtarpour et al. on-destructve estmaton of maze leaf area and weght 23 whch shows a consderable spread around the predcted values (Fg. 1 bottom row, left panel). All dfferences between observed and predcted fell wthn ± 3 SD of the mean dfference (Fg. 1 bottom row, rght panel). Lastly, we compared our predcton formula aganst the commonly used equaton by Montgomery (1911), mentoned n the ntroducton. The best estmate for constant A was Usng the value, our newly developed predcton formula resulted n a lower RMSE (35.6 vs. 38.5), a slghtly lower MAE (26.1 vs. 27.2), and an almost dentcal ndex of agreement (d = vs ). Fgure 1. Relatonshp between values predcted from the regresson equatons and measured values for leaf area, leaf fresh weght and leaf dry weght for the 459 leaves not n the tranng set. The left column of panels depcts the actual relatonshp based on predctons from equatons gven n Table 1, where the sold lne represents the lnear regresson of Y on X. The rght column of panels depcts the dfference between measured and predcted values, where the top (red) hashed lne represents the mean + 3 SD, and the bottom (blue) hashed lne the mean 3 SD.

6 24 Communcatons n Bometry and Crop Scence, 5(1) Table 2. Evaluaton of the equaton developed to predct maze leaf area. The test data set conssted of 459 leaves that were not part of the tranng data set. Treatment Root mean square error (RMSE) Mean absolute error (MAE) Index of agreement (d) umber of leaves cm 2 Plantng densty, plants ha Plant growth stage 5-leaf leaf Tasselng Mlk stage Plantng date 19 Aprl May May June All data Table 3. Evaluaton of the equaton developed to predct maze leaf fresh weght. The test data set conssted of 459 leaves that were not part of the tranng data set. Treatment Root mean square error (RMSE) g Mean absolute error (MAE) Index of agreement (d) umber of leaves Plantng densty, plants ha Plant growth stage 5-leaf leaf Tasselng Mlk stage Plantng date 19 Aprl May May June All data

7 Mokhtarpour et al. on-destructve estmaton of maze leaf area and weght 25 Table 4. Evaluaton of the equaton developed to predct maze leaf dry weght. The test data set conssted of 459 leaves that were not part of the tranng data set. Treatment Root mean square error (RMSE) g Mean absolute error (MAE) Index of agreement (d) umber of leaves Plantng densty, plants ha Plant growth stage 5-leaf leaf Tasselng Mlk stage Plantng date 19 Aprl May May June All data ACKOWLEDGEMETS We thank the Agrcultural and atural Resources Research Center, Golestan, Iran for fnancal support. Our especal thanks go to Mr. Fezbaksh and Mr. Hydar, Department of Seed and Plant Improvement, Agrcultural and atural Resources Research Center, Golestan, Iran for ther assstance n conductng the experments and data collecton. REFERECES Brch, C.J., Hammer, G.L., Rckert, K.G. (1998). Improved methods for predctng ndvdual leaf area and leaf senescence n maze (Zea mays). Australan Journal of Agrcultural Research 49, Burnham, K.P., Anderson, D.R. (2002). Model Selecton and Multmodel Inference: A Practcal Informaton- Theoretcal Approach. 2nd Edton. Sprnger-Verlag, ew York. Cho, Y.Y., Oh, S., Oh, M.M., Son, J.E. (2007). Estmaton of ndvdual leaf area, shoot fresh weght, and shoot dry weght of hydroponcally growth cucumbers (Cucums satvus L.) usng leaf length, wdth, and SPAD value. Scenta Hortculturae 111, Dwyer, L.M., Stewart, D.W. (1986). Leaf area development n feld-grown maze. Agronomy Journal 78, Elngs, A. (2000). Estmaton of leaf area n tropcal maze. Agronomy Journal 92, Gardner, F.P., Pearce, R.B., Mtchell, R.L. (1985). Physology of Crop Plants. Iowa State Unversty Press, Ames, IA. Hunt, R., Parsons, L.T. (1977). Plant growth-analyss: Further applcatons of a recent curvefttng program; Journal of Appled Ecology 14, Keatng, B.A., Wafula, B.M. (1992). Modelng the fully expanded area of maze leaves. Feld Crops Research 29, Kobayash, K., Salam, M.U. (2000). Comparng smulated and measured values usng mean squared devaton and ts components. Agronomy Journal 92,

8 26 Communcatons n Bometry and Crop Scence, 5(1) McKee, G.W. (1964). A coeffcent for computng leaf area n hybrd corn. Agronomy Journal 56, Pearce, R.B., Mock, J.H., Baley, T.B. (1975). Rapd method for estmatng leaf area per plant n maze. Crop Scence 15, Pekson, E. (2007). on-destructve leaf area estmaton for faba bean (Vca faba L.). Scntca Hortculturae 113, Potdar, M.V., Pawar, K.R. (1991). on-destructve leaf area estmaton n banana. Scntca Hortculturae 45, Serdar, U., Demrsoy, H. (2006). on-destructve leaf area estmaton n chestnut. Scntca Hortculturae 108, Stewart, D.W., Dwyer, L.M. (1999). Mathematcal characterzaton of leaf shape and area of maze hybrds. Crop Scence 39, Wllmott, C.J., Ackleson, S.G., Davs, R.E., Feddema, J.J., Klnk, D.R., Legates, K.M., O'Donnell, J., Rowe, C.M. (1985). Statstcs for the evaluaton and comparson of models. Journal of Geophyscal Research 90,